A reconciliation of empirical and mechanistic models of the air-sea gas transfer velocity

Models of the air-sea transfer velocity of gases may be either empirical or mechanistic. Extrapolations of empirical models to an unmeasured gas or to another water temperature can be erroneous if the basis of that extrapolation is flawed. This issue is readily demonstrated for the most well-known empirical gas transfer velocity models where the influence of bubble-mediated transfer, which can vary between gases, is not explicitly accounted for. Mechanistic models are hindered by an incomplete knowledge of the mechanisms of air-sea gas transfer. We describe a hybrid model that incorporates a simple mechanistic view—strictly enforcing a distinction between direct and bubble-mediated transfer—but also uses parameterizations based on data from eddy flux measurements of dimethyl sulphide (DMS) to calibrate the model together with dual tracer results to evaluate the model. This model underpins simple algorithms that can be easily applied within schemes to calculate local, regional, or global air-sea fluxes of gases.

A reconciliation of empirical and mechanistic models of the air-sea gas transfer velocity

Models of the air-sea transfer velocity of gases may be either empirical or mechanistic. Extrapolations of empirical models to an unmeasured gas or to another water temperature can be erroneous if the basis of that extrapolation is flawed. This issue is readily demonstrated for the most well-known empirical gas transfer velocity models where the influence of bubble-mediated transfer, which can vary between gases, is not explicitly accounted for. Mechanistic models are hindered by an incomplete knowledge of the mechanisms of air-sea gas transfer. We describe a hybrid model that incorporates a simple mechanistic view—strictly enforcing a distinction between direct and bubble-mediated transfer—but also uses parameterizations based on data from eddy flux measurements of dimethyl sulphide (DMS) to calibrate the model together with dual tracer results to evaluate the model. This model underpins simple algorithms that can be easily applied within schemes to calculate local, regional, or global air-sea fluxes of gases.

Murine Models of Diastolic Dysfunction and Heart Failure With Preserved Ejection Fraction

Left ventricular diastolic dysfunction leads to heart failure with preserved ejection fraction, an increasingly prevalent condition largely driven by modern day lifestyle risk factors. As heart failure with preserved ejection fraction accounts for almost one-half of all patients with heart failure, appropriate nonhuman animal models are required to improve our understanding of the pathophysiology of this syndrome and to provide a platform for preclinical investigation of potential therapies. Hypertension, obesity, and diabetes are major risk factors for diastolic dysfunction and heart failure with preserved ejection fraction. This review focuses on murine models reflecting this disease continuum driven by the aforementioned common risk factors. We describe various models of diastolic dysfunction and highlight models of heart failure with preserved ejection fraction reported in the literature. Strengths and weaknesses of the different models are discussed to provide an aid to translational scientists when selecting an appropriate model. We also bring attention to the fact that heart failure with preserved ejection fraction is difficult to diagnose in animal models and that, therefore, there is a paucity of well described animal models of this increasingly important condition.

Predicting polarization signatures for double-detonation and delayed-detonation models of Type Ia supernovae

Calculations of synthetic spectropolarimetry are one means to test multidimensional explosion models for Type Ia supernovae. In a recent paper, we demonstrated that the violent merger of a 1.1 and 0.9 M⊙ white dwarf binary system is too asymmetric to explain the low polarization levels commonly observed in normal Type Ia supernovae. Here, we present polarization simulations for two alternative scenarios: the sub-Chandrasekhar mass double-detonation and the Chandrasekhar mass delayed-detonation model. Specifically, we study a 2D double-detonation model and a 3D delayed-detonation model, and calculate polarization spectra for multiple observer orientations in both cases. We find modest polarization levels (<1 per cent) for both explosion models. Polarization in the continuum peaks at ∼0.1–0.3 per cent and decreases after maximum light, in excellent agreement with spectropolarimetric data of normal Type Ia supernovae. Higher degrees of polarization are found across individual spectral lines. In particular, the synthetic Si II λ6355 profiles are polarized at levels that match remarkably well the values observed in normal Type Ia supernovae, while the low degrees of polarization predicted across the O I λ7774 region are consistent with the non-detection of this feature in current data. We conclude that our models can reproduce many of the characteristics of both flux and polarization spectra for well-studied Type Ia supernovae, such as SN 2001el and SN 2012fr. However, the two models considered here cannot account for the unusually high level of polarization observed in extreme cases such as SN 2004dt.

Spiking neuron models of the medial and lateral superior olive for sound localisation

Sound localisation is defined as the ability to identify the position of a sound source. The brain employs two cues to achieve this functionality for the horizontal plane, interaural time difference (ITD) by means of neurons in the medial superior olive (MSO) and interaural intensity difference (IID) by neurons of the lateral superior olive (LSO), both located in the superior olivary complex of the auditory pathway. This paper presents spiking neuron architectures of the MSO and LSO. An implementation of the Jeffress model using spiking neurons is presented as a representation of the MSO, while a spiking neuron architecture showing how neurons of the medial nucleus of the trapezoid body interact with LSO neurons to determine the azimuthal angle is discussed. Experimental results to support this work are presented.

Do U.S. and Colombian macro factors improve the forecasting ability of unrestricted VAR models of the local term structure of interest rate?

Este estudio empírico compara la capacidad de los modelos Vectores auto-regresivos (VAR) sin restricciones para predecir la estructura temporal de las tasas de interés en Colombia -- Se comparan modelos VAR simples con modelos VAR aumentados con factores macroeconómicos y financieros colombianos y estadounidenses -- Encontramos que la inclusión de la información de los precios del petróleo, el riesgo de crédito de Colombia y un indicador internacional de la aversión al riesgo mejora la capacidad de predicción fuera de la muestra de los modelos VAR sin restricciones para vencimientos de corto plazo con frecuencia mensual -- Para vencimientos de mediano y largo plazo los modelos sin variables macroeconómicas presentan mejores pronósticos sugiriendo que las curvas de rendimiento de mediano y largo plazo ya incluyen toda la información significativa para pronosticarlos -- Este hallazgo tiene implicaciones importantes para los administradores de portafolios, participantes del mercado y responsables de las políticas

Sasakian quiver gauge theories and instantons on cones over lens 5-spaces

We consider SU(3)-equivariant dimensional reduction of Yang Mills theory over certain cyclic orbifolds of the 5-sphere which are Sasaki-Einstein manifolds. We obtain new quiver gauge theories extending those induced via reduction over the leaf spaces of the characteristic foliation of the Sasaki-Einstein structure, which are projective planes. We describe the Higgs branches of these quiver gauge theories as moduli spaces of spherically symmetric instantons which are SU(3)-equivariant solutions to the Hermitian Yang-Mills equations on the associated Calabi-Yau cones, and further compare them to moduli spaces of translationally-invariant instantons on the cones. We provide an explicit unified construction of these moduli spaces as Kahler quotients and show that they have the same cyclic orbifold singularities as the cones over the lens 5-spaces. (C) 2015 The Authors. Published by Elsevier B.V.

In vivo models of lung neutrophil activation. Comparison of mice and hamsters

BACKGROUND: Evidence suggests that both the migration and activation of neutrophils into the airway is of importance in pathological conditions such as pulmonary emphysema. In the present study, we describe in vivo models of lung neutrophil infiltration and activation in mice and hamsters. RESULTS: BALB/c and C57BL/6 mice were intranasally treated with lipopolysaccharide (0.3 mg/kg). Twenty-four hours after, animals were treated intranasally with N-Formyl-Met-Leu-Phe (0 to 5 mg/kg). Golden Syrian hamsters were treated intratracheally with 0.5 mg/kg of lipopolysaccharide. Twenty-four hours after, animals were treated intratracheally with 0.25 mg/kg of N-Formyl-Met-Leu-Phe. Both mice and hamster were sacrificed two hours after the N-Formyl-Met-Leu-Phe application. In both BALB/c and C57BL/6 mice, a neutrophil infiltration was observed after the sequential application of lipopolysaccharide and N-Formyl-Met-Leu-Phe. However, 5 times less neutrophil was found in C57BL/6 mice when compared to BALB/c mice. This was reflected in the neutrophil activation parameters measured (myeloperoxidase and elastase activities). Despite the presence of neutrophil and their activation status, no lung haemorrhage could be detected in both strains of mice. When compared with mice, the lung inflammation induced by the sequential application of lipopolysaccharide and N-Formyl-Met-Leu-Phe was much greater in the hamster. In parallel with this lung inflammation, a significant lung haemorrhage was also observed. CONCLUSIONS: Both mouse and hamster can be used for pharmacological studies of new drugs or other therapeutics agents that aimed to interfere with neutrophil activation. However, only the hamster model seems to be suitable for studying the haemorrhagic lung injury process

The role of intracellular calcium perturbations in muscle damage and dysfunction in mouse models of muscular dystrophy

Duchenne muscular dystrophy (DMD) is a neuromuscular disease caused by mutations in the dystrophin gene. DMD is clinically characterized by severe, progressive and irreversible loss of muscle function, in which most patients lose the ability to walk by their early teens and die by their early 20’s. Impaired intracellular calcium (Ca2+) regulation and activation of cell degradation pathways have been proposed as key contributors to DMD disease progression. This dissertation research consists of three studies investigating the role of intracellular Ca2+ in skeletal muscle dysfunction in different mouse models of DMD. Study one evaluated the role of Ca2+-activated enzymes (proteases) that activate protein degradation in excitation-contraction (E-C) coupling failure following repeated contractions in mdx and dystrophin-utrophin null (mdx/utr-/-) mice. Single muscle fibers from mdx/utr-/- mice had greater E-C coupling failure following repeated contractions compared to fibers from mdx mice. Moreover, protease inhibition during these contractions was sufficient to attenuate E-C coupling failure in muscle fibers from both mdx and mdx/utr-/- mice. Study two evaluated the effects of overexpressing the Ca2+ buffering protein sarcoplasmic/endoplasmic reticulum Ca2+-ATPase 1 (SERCA1) in skeletal muscles from mdx and mdx/utr-/- mice. Overall, SERCA1 overexpression decreased muscle damage and protected the muscle from contraction-induced injury in mdx and mdx/utr-/- mice. In study three, the cellular mechanisms underlying the beneficial effects of SERCA1 overexpression in mdx and mdx/utr-/- mice were investigated. SERCA1 overexpression attenuated calpain activation in mdx muscle only, while partially attenuating the degradation of the calpain target desmin in mdx/utr-/- mice. Additionally, SERCA1 overexpression decreased the SERCA-inhibitory protein sarcolipin in mdx muscle but did not alter levels of Ca2+ regulatory proteins (parvalbumin and calsequestrin) in either dystrophic model. Lastly, SERCA1 overexpression blunted the increase in endoplasmic reticulum stress markers Grp78/BiP in mdx mice and C/EBP homologous protein (CHOP) in mdx and mdx/utr-/- mice. Overall, findings from the studies presented in this dissertation provide new insight into the role of Ca2+ in muscle dysfunction and damage in different dystrophic mouse models. Further, these findings support the overall strategy for improving intracellular Ca2+ control for the development of novel therapies for DMD.

Role of chemerin and its receptors in mouse models of tumorigenesis

Dissertação de Mestrado, Oncobiologia: Mecanismos Moleculares do Cancro, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2015

Chebanov law and Vakar formula in mathematical models of complex systems

Ecological models written in a mathematical language L(M) or model language, with a given style or methodology can be considered as a text. It is possible to apply statistical linguistic laws and the experimental results demonstrate that the behaviour of a mathematical model is the same of any literary text of any natural language. A text has the following characteristics: (a) the variables, its transformed functions and parameters are the lexic units or LUN of ecological models; (b) the syllables are constituted by a LUN, or a chain of them, separated by operating or ordering LUNs; (c) the flow equations are words; and (d) the distribution of words (LUM and CLUN) according to their lengths is based on a Poisson distribution, the Chebanov's law. It is founded on Vakar's formula, that is calculated likewise the linguistic entropy for L(M). We will apply these ideas over practical examples using MARIOLA model. In this paper it will be studied the problem of the lengths of the simple lexic units composed lexic units and words of text models, expressing these lengths in number of the primitive symbols, and syllables. The use of these linguistic laws renders it possible to indicate the degree of information given by an ecological model.

Challenges with in vitro and in vivo experimental models of urinary bladder cancer for novel drug discovery

Urinary bladder cancer (UBC) is the second most frequent malignancy of the urinary system and the ninth most common cancer worldwide, affecting individuals over the age of 65. Several investigations have embarked on advancing knowledge of the mechanisms underlying urothelial carcinogenesis, understanding the mechanisms of antineoplastic drugs resistance and discovering new antineoplastic drugs. In vitro and in vivo models are crucial for providing additional insights into the mechanisms of urothelial carcinogenesis. With these models, various molecular pathways involved in urothelial carcinogenesis have been discovered, allowing therapeutic manipulation.

Occurrence and abundance models of threatened plant species: Applications to mitigate the impact of hydroelectric power dams

Species occurrence and abundance models are important tools that can be used in biodiversity conservation, and can be applied to predict or plan actions needed to mitigate the environmental impacts of hydropower dams. In this study our objectives were: (i) to model the occurrence and abundance of threatened plant species, (ii) to verify the relationship between predicted occurrence and true abundance, and (iii) to assess whether models based on abundance are more effective in predicting species occurrence than those based on presence–absence data. Individual representatives of nine species were counted within 388 randomly georeferenced plots (10 m × 50 m) around the Barra Grande hydropower dam reservoir in southern Brazil. We modelled their relationship with 15 environmental variables using both occurrence (Generalised Linear Models) and abundance data (Hurdle and Zero-Inflated models). Overall, occurrence models were more accurate than abundance models. For all species, observed abundance was significantly, although not strongly, correlated with the probability of occurrence. This correlation lost significance when zero-abundance (absence) sites were excluded from analysis, but only when this entailed a substantial drop in sample size. The same occurred when analysing relationships between abundance and probability of occurrence from previously published studies on a range of different species, suggesting that future studies could potentially use probability of occurrence as an approximate indicator of abundance when the latter is not possible to obtain. This possibility might, however, depend on life history traits of the species in question, with some traits favouring a relationship between occurrence and abundance. Reconstructing species abundance patterns from occurrence could be an important tool for conservation planning and the management of threatened species, allowing scientists to indicate the best areas for collection and reintroduction of plant germplasm or choose conservation areas most likely to maintain viable populations.